JAB002.3 lum & cell count analysis

RealTime-Glo vs direct cell counts via fluorescence microscopy

Analysis of PC9.1 cells treated with multiple drugs and drug concentrations using RT-glo

library(diprate)
d <- read.csv("~/dropbox-vu/temp/lum_cellcount_JAB002-3.csv", row.names=1)

Clean up data

d[d$drug_conc == "NaN", "drug_conc"] <- NA
d$drug_conc <- as.numeric(d$drug_conc)
d[d$drug == "", "drug"] <- NA

cn <- colnames(d)

cn <- gsub("drug_", "drug1.", cn)
cn <- gsub("drug$", "drug1", cn)
cn <- gsub("_", ".", cn)
colnames(d) <- cn

d[is.na(d$drug1.conc), "drug1.conc"] <- 0

fixTime <- function(...) strptime(format="%m-%d-%Y %I:%M %p", ...)
TxTime <- fixTime(min(d$image.time))
d$time <- signif(as.numeric(difftime(fixTime(d$image.time), TxTime, units="hours")),3)
d <- d[order(d$well,d$time),]

# remove first time point
# d <- d[d$plate.id != 1,]

ctrl <- d[d$drug1.conc==0,]

temp <- plotGC(ctrl$time, ctrl$cell.count, ctrl$well, main="Cell counts")

temp <- plotGC(ctrl$time, ctrl$RLU, ctrl$well, main="Luminescence")

drugs <- unique(d$drug1)
drugs <- drugs[!is.na(drugs)]

a <- lapply(drugs, function(dr) prepDataCLD(dat=d, drug=dr))

par(mfrow=c(3,3))
temp <- lapply(a, function(z) do.call(plotGC, append(getGCargs(z), list(rep=z$drug1.conc, main=unique(z$drug1)))))